Artificial Neural Network Modeling of the Spontaneous Combustion Occurring in the Industrial-scale Coal Stockpiles with 10-18 mm Coal Grain Sizes

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dc.contributor.authorOzdeniz, A. H.
dc.contributor.authorYilmaz, N.
dc.date.accessioned2020-03-26T17:37:54Z
dc.date.available2020-03-26T17:37:54Z
dc.date.issued2009
dc.departmentSelçuk Üniversitesien_US
dc.description.abstractCompanies consuming large amounts of coal should work with coal stocks in order to not face problems due to production delays. The industrial-scale stockpiles formed for the aforementioned reasons cause environmental problems and economic losses for the companies. This study was performed in a coal stock area of a large company in Konya, which uses large amounts of coal in its manufacturing units. The coal stockpile with 5 m width, 10 m length, 3 m height, and having 120 tons of weight was formed in the coal stock area of the company. The inner temperature data of the stockpile was recorded by 17 temperature sensors placed inside the stockpile at certain points. In order to achieve this goal, the electrical signal conversion of temperatures sensed by 17 temperature sensors placed in certain points inside the coal stockpile, the transfer of these electrical signals into computer media by using analog-digital conversion unit after applying necessary filtration and upgrading processes, and the record of these information into a database in particular time intervals are provided. Additionally, the data relating to the air temperature, air humidity, atmospheric pressure, wind velocity, and wind direction that are the parameters affecting the coal stockpile were also recorded. Afterwards, these measurement values were used for training and testing of an artificial neural network model. Comparison of the experimental and artificial neural network results, accuracy rates of training and testing were found to be 99.5% and 99.17%, respectively. It is shown that possible coal stockpile behavior with this artificial neural network model is powerfully estimated.en_US
dc.description.sponsorshipCoordinatorship of Selcuk University's Scientific ResearchSelcuk Universityen_US
dc.description.sponsorshipThis work was supported by the Coordinatorship of Selcuk University's Scientific Research Projects.en_US
dc.identifier.doi10.1080/15567030802092817en_US
dc.identifier.endpage1435en_US
dc.identifier.issn1556-7036en_US
dc.identifier.issue16en_US
dc.identifier.scopusqualityQ2en_US
dc.identifier.startpage1425en_US
dc.identifier.urihttps://dx.doi.org/10.1080/15567030802092817
dc.identifier.urihttps://hdl.handle.net/20.500.12395/23297
dc.identifier.volume31en_US
dc.identifier.wosWOS:000268628200001en_US
dc.identifier.wosqualityQ2en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherTAYLOR & FRANCIS INCen_US
dc.relation.ispartofENERGY SOURCES PART A-RECOVERY UTILIZATION AND ENVIRONMENTAL EFFECTSen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.selcuk20240510_oaigen_US
dc.subjectartificial neural networken_US
dc.subjectcoalen_US
dc.subjectspontaneous combustionen_US
dc.subjectstockpileen_US
dc.titleArtificial Neural Network Modeling of the Spontaneous Combustion Occurring in the Industrial-scale Coal Stockpiles with 10-18 mm Coal Grain Sizesen_US
dc.typeArticleen_US

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